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Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>

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Publication Date
Wed Jul 24 2024
Journal Name
Annals Of Parasitology
In vitro efficacy of different concentrations of lupeol on old world Leishmania donovani
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Leishmaniosis is a tropical neglected parasitic disease that is endemic in many countries, including Middle East, with no existing effective vaccines. The bite of female sand-fly transmits the causative agent, Leishmania spp., to humans. High toxicity, resistance and treatment failure of the available chemotherapy against visceral leishmaniosis demands the investigation of new anti-leishmanial compounds. Lupeol is a form of triterpene isolated from several medicinal plants and possesses an antimicrobial property. In this study, cytotoxic effect of lupeol was screened against the mammalian amastigotes form and insect promastigote form of Leishmania donovani, following three cycles of incubation at different concentrations by MTT assay. Resul

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Publication Date
Sun Jun 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Kinetic Study and Simulation of Oleic Acid Esterification in Different Type of Reactors
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Esterification reaction is most important reaction in biodiesel production. In this study, oleic acid was used as a suggested feedstock to study and simulate production of biodiesel. Batch esterification of oleic acid was carried out at operating conditions; temperature from 40 to 70 °C, ethanol to oleic acid molar ratio from 1/1 to 6/1, H2SO4 as the catalyst 1 and 5% wt of oleic acid, reaction time up to 180 min. The optimum conditions for the esterification reaction were molar ratio of ethanol/oleic acid 6/1, 5%wt H2SO4 relative to oleic acid, 70 °C, 90 min and conversion of oleic 0.92. The activation energy for the suggested model was 26625 J/mole for forward reaction and 42189 J/mole for equilibrium constant. The obtained results s

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Publication Date
Sat Mar 28 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Different Electrodes Connections in Electrocoagulation of Synthetic Blow down Water of Cooling Tower
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In this research, the performance of electrocoagulation (EC) using aluminum (Al) electrodes with   Monopolar- parallel (MP-P), and bipolar - series (BP-S) arrangement for simultaneous removal of dissolved silica, and hardness ions (calcium, and magnesium) from synthetic blowdown water of cooling tower were investigated. The effects of current density, initial pH and time of electrolysis on the removal efficiency were studied in a batch stirred unit to find out the best-operating conditions. The obtained results for each target species are evidence that BP-S approach is the best for both electrodes configuration operated at a Current density of 1mA/cm2 through 30 min of treatment and pH=10 with the removal of

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Estimators for the Parameter of the Inverted Exponential Distribution Under different Double informative priors
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In this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.

Additionally Maximum likelihood estimation method

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Publication Date
Wed Jan 01 2014
Journal Name
Babylon University Journal\applied Pure Sciences
Detection of the perfect condition to produce the tannase from Aspergillus niger at different medium
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Publication Date
Sat Feb 12 2022
Journal Name
Engineering, Technology &amp; Applied Science Research
The Effect of Different Curing Temperatures on the Properties of Geopolymer Reinforced with Micro Steel Fibers
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In this study, geopolymer mortar was designed in various experimental combinations employing 1% micro steel fibers and was subjected to different temperatures, according to the prior works of other researchers. The geopolymer mortar was developed using a variety of sustainable material proportions (fly ash and slag) to examine the influence of fibers on its strength. The fly ash weight percentage was 50%, 60%, and 70% by slag weight to study its effect on the geopolymer mortar's properties. The optimal ratio produced the most significant results when mixed at a 50:50 ratio of fly ash and slag with 1% micro steel fibers at curing temperature 240oC for 4 hours through two days. The compressive strength of the geopolymer mortar increas

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
The effect of using different fibres on the impact-resistance of slurry infiltrated fibrous concrete (SIFCON)
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Abstract<p>Slurry infiltrated fibrous concrete (SIFCON) is a modern type of fibre reinforced concrete (FRC). It has unique properties; SIFCON is superior in compressive strength, flexural strength, tensile strength, impact resistance, energy absorption and ductility. Because of this superiority in these characteristics, SIFCON was qualified for applications of special structures, which require resisting sudden dynamic loads such as explosions and earthquakes. The main aim of this investigation is to determine the effect of fibre type on the apparent density of SIFCON and on performance under impact load. In this investigation, hook-end steel fibre and polyolefin fibre were used. Purely once and </p> ... Show More
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Developing strategic leadership practices in the light of transparency and organizational citizenship behavior - A field study of a sample of the staff of the Office of the Inspector General at the Iraqi Ministry of Culture
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Diversity the terms and practice the organizational filed with different concepts and environment, which Iraqi environment part from them. Some organizational in Iraqi environment leave its basic oriented to agreement with the leader desire, their fore this research focus tow basic variable (organizational citizenship behavior & transparence), we supposition which is dependent to explanation the response variable (strategic leadership). The results justification in part and not justification in another part. For example the organizational citizenship behavior effect on some parte of the strategic leadership. The transparence have faraway to fly from the relation with organizational citizenship behavior and strategic leadershi

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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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